使用总和时，R中找不到错误

发布于 2025-02-01 05:09:47 字数 741 浏览 4 评论 0原文

我一直在尝试使用数据集产生一些可视化。我首先在数据框架中添加了一些新列：

ads <- ads %>% mutate(estimated_audience_size_mean = round(rowMeans(ads[,17:18]), -1),
                      impressions_mean = round(rowMeans(ads[,19:20]), -1),
                      spend_mean = round(rowMeans(ads[,21:22]), -1))

现在，当我从“环境”选项卡中查看广告时，我可以看到创建的三个新列。但是，当我尝试在下面运行代码时，我会收到以下错误，

pages <- ads %>%
   group_by(page_name) %>%
   sum(spend_mean) %>%
   ungroup() %>%
   arrange(desc(n)) %>%
   slice(1:15)

我会收到以下错误：

object'spent_mean'找不到

我尝试安装运算符库，然后是magrittr。并替换为|＆gt;的％＆gt;。还用广告$ page_name和ads $ speent_mean替换page_name and vente_mean。但是似乎没有任何作用。如何使第二个块的代码工作？

原文

I have been trying to produce some visualizations using a dataset. I first added some new columns to the dataframe:

ads <- ads %>% mutate(estimated_audience_size_mean = round(rowMeans(ads[,17:18]), -1),
                      impressions_mean = round(rowMeans(ads[,19:20]), -1),
                      spend_mean = round(rowMeans(ads[,21:22]), -1))

Now, when I view ads from the environment tab, I can see the three new columns created. However, when I try running the code below, I get the following error

pages <- ads %>%
   group_by(page_name) %>%
   sum(spend_mean) %>%
   ungroup() %>%
   arrange(desc(n)) %>%
   slice(1:15)

I get the following error:

object 'spend_mean' not found

I have tried installing operators library followed by magrittr. And replaced %>% with |>. Also replaced page_name and spend_mean with ads$page_name and ads$spend_mean. But nothing seems to work. How can I make the second code of chunk work?

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两仪 2025-02-08 05:09:47

正如Limey在评论中分享的那样，将“总和”函数包装在突变中可以做到这一点。

pages <- ads %>%
  group_by(page_name) %>%
  mutate(page_spend_mean = sum(spend_mean)) %>%
  ungroup() %>%
  arrange(desc(page_spend_mean)) %>%
  slice(1:15)

As shared by Limey in the comments, wrapping the sum function in mutate did the trick.

pages <- ads %>%
  group_by(page_name) %>%
  mutate(page_spend_mean = sum(spend_mean)) %>%
  ungroup() %>%
  arrange(desc(page_spend_mean)) %>%
  slice(1:15)

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